231 lines
6.8 KiB
Plaintext
231 lines
6.8 KiB
Plaintext
{
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"cells": [
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{
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"cell_type": "markdown",
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"id": "56c86bae-1d3c-4c01-b5d6-c8879fec1954",
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"metadata": {},
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"source": [
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"# Wiki Summarizer\n",
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"\n",
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"This Project takes the name of a topic as input, and checks if the corresponding wiki-page exists. If it does, it parses the web page, and outputs a summary created using the GPT-4o-mini model. \n",
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"\n",
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"Concepts used: \n",
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"- Web Scraping via Beautiful Soup\n",
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"- User and System Prompts\n",
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"- Use of Open AI GPT-4o-mini via API key"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "4820830e-b3b4-426e-b1a2-518e7c7f6c1a",
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"metadata": {},
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"outputs": [],
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"source": [
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"# imports\n",
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"\n",
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"import os\n",
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"import requests\n",
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"from dotenv import load_dotenv\n",
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"from bs4 import BeautifulSoup\n",
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"from IPython.display import Markdown, display\n",
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"from openai import OpenAI"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "2cd7ad51-396c-45c5-9089-f7b21a19da50",
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"metadata": {},
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"outputs": [],
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"source": [
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"# Load environment variables in a file called .env\n",
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"\n",
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"load_dotenv(override=True)\n",
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"api_key = os.getenv('OPENAI_API_KEY')\n",
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"\n",
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"# Check the key\n",
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"\n",
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"if not api_key:\n",
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" print(\"No API key was found - please head over to the troubleshooting notebook in this folder to identify & fix!\")\n",
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"elif not api_key.startswith(\"sk-proj-\"):\n",
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" print(\"An API key was found, but it doesn't start sk-proj-; please check you're using the right key - see troubleshooting notebook\")\n",
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"elif api_key.strip() != api_key:\n",
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" print(\"An API key was found, but it looks like it might have space or tab characters at the start or end - please remove them - see troubleshooting notebook\")\n",
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"else:\n",
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" print(\"API key found and looks good so far!\")"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "689421a0-20a1-428b-a8b8-fa239fa6f633",
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"metadata": {},
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"outputs": [],
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"source": [
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"# creating an instance\n",
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"openai = OpenAI()"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "401901ae-7639-4190-98fd-e69374084723",
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"metadata": {},
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"outputs": [],
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"source": [
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"def isWiki(url):\n",
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" \"\"\"\n",
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" Check whether a Wikipedia page exists for a given topic, and \n",
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" returns a Boolean value.\n",
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" \"\"\"\n",
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" response = requests.get(url)\n",
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"\n",
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" if response.status_code != 200:\n",
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" return False\n",
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" \n",
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" return True"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "7cdb14d3-05ea-4de2-a475-d49a5731692e",
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"metadata": {},
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"outputs": [],
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"source": [
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"# A class to represent a Webpage\n",
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"\n",
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"# Some websites need you to use proper headers when fetching them:\n",
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"headers = {\n",
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" \"User-Agent\": \"Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/117.0.0.0 Safari/537.36\"\n",
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"}\n",
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"\n",
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"class Website:\n",
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"\n",
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" def __init__(self, url):\n",
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" \"\"\"\n",
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" Create this Website object from the given url using the BeautifulSoup library\n",
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" \"\"\"\n",
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" self.url = url\n",
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" response = requests.get(url, headers=headers)\n",
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" soup = BeautifulSoup(response.content, 'html.parser')\n",
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" self.title = soup.title.string if soup.title else \"No title found\"\n",
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" for irrelevant in soup.body([\"script\", \"style\", \"img\", \"input\"]):\n",
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" irrelevant.decompose()\n",
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" self.text = soup.body.get_text(separator=\"\\n\", strip=True)"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "7f6ed50e-0fb5-479e-9845-f62cf25980f7",
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"metadata": {},
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"outputs": [],
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"source": [
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"system_prompt = \"You are an educational assistant tasked with helping users understand topics\\\n",
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"by providing succinct and clear summaries of requested data. Ignore navigation-related text\\\n",
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"and provide answers in markdown format\""
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "b2d77dd9-a94f-49c1-a1be-11d157bd37fb",
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"metadata": {},
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"outputs": [],
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"source": [
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"# A function that writes a User Prompt that asks for summaries of wiki pages:\n",
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"\n",
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"def user_prompt_for(wiki):\n",
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" user_prompt = f\"You are looking at a Wikipedia page titled {wiki.title}\"\n",
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" user_prompt += \"\\nThe contents of this page is as follows; \\\n",
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"please provide a short summary of this website in markdown.\\n\"\n",
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" user_prompt += wiki.text\n",
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" return user_prompt"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "0d23bcc4-1d89-4bd4-9809-d3a1819aa919",
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"metadata": {},
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"outputs": [],
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"source": [
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"def messages_for(wiki):\n",
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" return [\n",
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" {\"role\": \"system\", \"content\": system_prompt},\n",
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" {\"role\": \"user\", \"content\": user_prompt_for(wiki)}\n",
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" ]"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "971bd7fb-2ff8-4494-b386-de69a39c24ff",
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"metadata": {},
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"outputs": [],
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"source": [
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"def summarize(url):\n",
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" website = Website(url)\n",
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" response = openai.chat.completions.create(\n",
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" model = \"gpt-4o-mini\",\n",
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" messages = messages_for(website)\n",
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" )\n",
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" return response.choices[0].message.content"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "a8fdf9f2-f49e-4d06-ac9e-dfcb8da33d60",
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"metadata": {},
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"outputs": [],
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"source": [
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"def display_summary(topic):\n",
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" url = f\"https://en.wikipedia.org/wiki/{topic}\"\n",
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" if isWiki(url):\n",
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" summary = summarize(url)\n",
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" display(Markdown(summary))\n",
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" else:\n",
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" print('A Wikipedia page does not exist for this topic')\n",
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" "
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "f4758ef0-9b7c-4d3e-9131-e3284dc76b6b",
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"metadata": {
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"scrolled": true
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},
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"outputs": [],
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"source": [
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"topic = input('Enter the name of Wikipedia page for which you would like a summary: ').strip()\n",
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"display_summary(topic)"
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]
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}
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],
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"metadata": {
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"kernelspec": {
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"display_name": "Python 3 (ipykernel)",
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"language": "python",
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"name": "python3"
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},
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"language_info": {
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"codemirror_mode": {
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"name": "ipython",
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"version": 3
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},
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"file_extension": ".py",
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"mimetype": "text/x-python",
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.11.11"
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}
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},
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"nbformat": 4,
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"nbformat_minor": 5
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}
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